Front. Syst. Neurosci., 15 November 2016 |
Brain Computation Is Organized via Power-of-Two-Based Permutation Logic
Kun Xie1,2†, Grace E. Fox1†, Jun Liu1,2†, Cheng Lyu3,4†, Jason C. Lee1†, Hui Kuang1†, Stephanie Jacobs1, Meng Li1,2, Tianming Liu3, Sen Song5 and Joe Z. Tsien1,2*
1Brain and Behavior Discovery Institute and Department of Neurology, Medical College of Georgia, Augusta University, Augusta, GA, USA
2The Brain Decoding Center, Banna Biomedical Research Institute, Yunnan Academy of Science and Technology, Yunnan, China
3Department of Computer Science and Brain Imaging Center, University of Georgia, Athens, GA, USA
4School of Automation, Northwestern Polytechnical University, Xi’an, China
5McGovern Institute for Brain Research and Center for Brain-Inspired Computing Research, Tsinghua University, Beijing, China
Abstract
There is considerable scientific interest in understanding how cell assemblies—the long-presumed computational motif—are organized so that the brain can generate intelligent cognition and flexible behavior. The Theory of Connectivity proposes that the origin of intelligence is rooted in a power-of-two-based permutation logic (N = 2i–1), producing specific-to-general cell-assembly architecture capable of generating specific perceptions and memories, as well as generalized knowledge and flexible actions. We show that this power-of-two-based permutation logic is widely used in cortical and subcortical circuits across animal species and is conserved for the processing of a variety of cognitive modalities including appetitive, emotional and social information. However, modulatory neurons, such as dopaminergic (DA) neurons, use a simpler logic despite their distinct subtypes. Interestingly, this specific-to-general permutation logic remained largely intact although NMDA receptors—the synaptic switch for learning and memory—were deleted throughout adulthood, suggesting that the logic is developmentally pre-configured. Moreover, this computational logic is implemented in the cortex via combining a random-connectivity strategy in superficial layers 2/3 with nonrandom organizations in deep layers 5/6. This randomness of layers 2/3 cliques—which preferentially encode specific and low-combinatorial features and project inter-cortically—is ideal for maximizing cross-modality novel pattern-extraction, pattern-discrimination and pattern-categorization using sparse code, consequently explaining why it requires hippocampal offline-consolidation. In contrast, the nonrandomness in layers 5/6—which consists of few specific cliques but a higher portion of more general cliques projecting mostly to subcortical systems—is ideal for feedback-control of motivation, emotion, consciousness and behaviors. These observations suggest that the brain’s basic computational algorithm is indeed organized by the power-of-two-based permutation logic. This simple mathematical logic can account for brain computation across the entire evolutionary spectrum, ranging from the simplest neural networks to the most complex.
FREE PDF GRATIS: Frontiers in Systems Neuroscience
